Statistical Reasoning

Introduction to statistical reasoning

Klinkenberg

University of Amsterdam

2025-09-01

Statistical Reasoning

Course setup

Lectures: On campus / Online / Video recording
Preparatory Assignment: Submit and reflect in canvas
Tutorials: For your support and in class progress check (you can mis max 3 tutorials)
Exam: Knowledge and skills

in class progress check

Grading

\(\text{Final grade} = 0.9 \times \text{exam grade} + 0.1 \times \text{Preparatory Assignment}\)

Exam
Preparatory Assignment (VO in Dutch)

Preparatory Assignment

11 PA’s/VO’s in total
You need to have done the PA with effort and reflect on your progress.

\[\text{PA points} = \frac{\text{Number of PA's done}}{11}\]

Learning

Course changes

Changes based on feedback, course evaluation, redesign and DEI project.

Textual instructions added to all SPSS content in the book.
ANOVA chapter example changed from Jolie & Clooney to Vaccine acceptance to be less gender stereo typed.
Moderation with regression chapters, analysis now all done with PROCESS

Organisational changes

Tutorial attendance now mandatory (mis max 3)
Resit now in March

Reasoning in statistics

Statistical Literacy

Knowledge (Basic understanding of concepts)
- Identify
- Describe
Skils (Ability to work with statistical tools)
- Translate
- Interpret
- Read
- Compute

Statistical Reasoning

Understanding
- Explain why
- Explain how

Statistical thinking

Apply
- What methods to use in a specific situation
Critique
- Comment and reflect on work of others
Evaluate
- Assigning value to work
Generalize
- What does variation mean in the large scheme of life

Empirical Cycle

By Adriaan de Groot

The components

Observation
- Idea for hypothesis
Induction
- General rule
- Hypothesis
Deduction
- Expectation / Prediction
- Operationalization

Testing
- Test hypothesis
- Compare data to prediction
Evaluation
- Interpret results in terms of hypothesis

Explained by Annemarie Zandscholten

Experiment

Heads

bit.ly/2j54A2U

Emperical Cycle

Observation Patiënt is showing post traumatic symptoms
Induction Can we diagnose PTSD
Deduction \(H_0\): P: fair coin → C: patiënt is balanced
Deduction \(H_A\): P: Unfair coin → C: patiënt is unbalanced
Deduction \(H_A\): P: data \(\neq\) EV → C: is unbalanced
Testing Choose \(\alpha\) and Power
Evaluation Make a decision

Null distribution

Let’s analyse the null distribution of the results.

Google sheet

Distributions

What is the difference between

Population distribution
Sample distribution
Sampling distribution

Binomial distribution

\[ {n\choose k}p^k(1-p)^{n-k}\]

\[ {n\choose k} = \frac{n!}{k!(n-k)!} \]

With values:

n = 10   # Sample size
k = 0:10 # Discrete probability space
p = .5   # Probability of head

Probabilities

Testing

I landed 2 times head. Can we conclude PTSD?

As you can see from the distribution of healthy coins, we cannot conclude that by definition.
What we can do is indicate how rare 2 is in a healthy population.

Null distribution

End

Contact